Reliable Omnidirectional Depth Map Generation for Indoor Mobile Robot Navigation Via a Single Perspective Camera

  • Chuanjiang Luo
  • Feng Zhu
  • Zelin Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4282)


This paper deals with the problem of finding the largest navigable areas around a mobile robot, which is important for navigation and action planning. We propose a method to obtain reliable dense 3D maps using a novel omnidirectional stereo vision system. The vision system is composed of a perspective camera and two hyperbolic mirrors. Once the system has been calibrated and two image points respectively projected by upper and below mirrors are matched, the 3D coordinate of the space point can be acquired by means of triangulation. To achieve the largest reliable dense matching, our method are divided into three steps. First reliable FX-dominant matching; then feature matching and ambiguous removal; finally the remaining points between features are matched using dynamic time warping(DTW) with modified energy functions adapted well to our system. Experiments show that this proposed vision system is feasible as a practical stereo sensor for accurate 3D map generation.


Mobile Robot Dynamic Time Warping Feature Match Stereo Vision Stereo Match 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chuanjiang Luo
    • 1
    • 2
  • Feng Zhu
    • 1
  • Zelin Shi
    • 1
  1. 1.Optical-Electronic Information Laboratory, Shenyang Institute of AutomationChinese Academy of SciencesShenyangChina
  2. 2.Graduate School of the Chinese Academy of SciencesBeijingChina

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